Skip to main navigation Skip to search Skip to main content

Precise monodisperse droplet generation by pressure-driven microfluidic flows

  • Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

In a T-junction microdroplet generator, as monodisperse droplets are formed for the droplet digital polymerase chain reaction (PCR), a mathematical model which can describe the nonlinear relation of droplet generation under pressure-driven microfluidic flows is established. For various viscosity of the fluids, the relation between the droplet length and the driving-pressure ratio is measured at a low capillary number (Ca < 0.01) of droplet generation. It can be observed that the droplet length varies nonlinearly with the driving-pressure ratio for a specific geometry of the T-junction. In particular, the relation between the droplet length and the driving-pressure ratio is tested experimentally for different geometries of the T-junctions. At low capillary numbers, the nonlinear relation between the droplet length and the driving-pressure ratio is basically determined by the geometrical parameters of the T-junction. Most importantly, a closed-loop control droplet microfluidic system is demonstrated, and the size of the droplets can be controlled more accurately by pressure-driven flows. The control precision of the droplet size is quantitatively studied for a wide range of typical conditions of droplet generation. In particular, the relative standard deviation of the droplet size for various flow conditions is less than 2%, which is of great importance for improving the detection accuracy of nucleic acid based on the droplet digital PCR.

Original languageEnglish
Article number117206
JournalChemical Engineering Science
Volume248
DOIs
StatePublished - 2 Feb 2022

Keywords

  • Accuracy
  • Closed-loop control
  • Droplet
  • Pressure-driven flows
  • Size

Fingerprint

Dive into the research topics of 'Precise monodisperse droplet generation by pressure-driven microfluidic flows'. Together they form a unique fingerprint.

Cite this